Running head: REDUCING HAPIs 1
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Running head: REDUCING HAPIs 1 Reducing Hospital-Acquired Pressure Injuries through the implementation of the Leaf Patient Monitoring System Meghan Kelley Jacksonville University DNP Chair: Ashlee Loewen, DNP, APRN, FNP-C Additional Team Member: Peter Wludyka, PhD
Transcript of Running head: REDUCING HAPIs 1
Running head: REDUCING HAPIs 1
Reducing Hospital-Acquired Pressure Injuries
through the implementation of the Leaf Patient Monitoring System
Meghan Kelley
Jacksonville University
DNP Chair: Ashlee Loewen, DNP, APRN, FNP-C
Additional Team Member: Peter Wludyka, PhD
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A DNP PROJECT
Reducing Hospital-Acquired Pressure Injuries
through the implementation of the Leaf Patient Monitoring System
A Project Presented to the Faculty of Keigwin School of Nursing
Jacksonville University
In partial fulfillment of the requirements
For the Degree of Doctor of Nursing Practice
by
Meghan Kelley
Approved: Ashlee Loewen, DNP, APRN, FNP-C
DNP Chair
Approved: Lila de Tantillo, PhD, MS, FNP-BC
DNP Secondary Advisor and Reader
Approved: Lindsay Wolf, DNP, APRN, CPNP-PC, CNE, CLC
Graduate Director for DNP Program, Keigwin School of Nursing
Approved: Leigh Hart, PhD, APRN-BC
Associate Dean, Keigwin School of Nursing
Date: April 29, 2021
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Table of Contents
Introduction 5
Nursing-Sensitive Implications 5
Financial Implications 7
Significance 7
Purpose 9
Framework 10
Theoretical Framework 10
Quality Improvement Model 12
Definition of Terms 12
Review of Literature 13
Risk Assessment 14
Turn Period 16
Multicomponent Interventions 18
Patient Monitoring Technology 20
Synthesis of Findings 26
Project Description 27
Outcomes 27
Intervention 28
Technology 28
Plan 29
Key Stakeholders 29
Setting and Population 30
Education 31
Fiscal Consideration 33
Confidentiality 33
Institutional Review Board Plan 34
Do 34
Measures 35
Study 36
Evaluation Plan 36
Act 37
Sustainability 37
Timeline 37
Findings 39
Objectives Met 39
Objectives Not Met 40
Data Analysis 40
HAPI Data Analysis 40
Turning Compliance Data Analysis 41
Facilitators and Positive Outcomes 41
Barriers and Negative Outcomes 42
Adverse Events 44
Recommendations 44
Discussion 45
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References 47
Appendix A 52
Appendix B 53
Appendix C 54
Appendix D 55
Appendix E 72
Appendix F 74
Appendix G 75
Appendix H 76
Appendix I 77
Appendix J 78
Appendix K 79
Appendix L 80
Appendix M 81
Appendix N 82
Appendix O 84
Appendix P 85
Appendix Q 86
Appendix R 87
Appendix S 88
Appendix T 89
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Reducing Hospital-Acquired Pressure Injuries through the implementation of the Leaf Patient
Monitoring System
Introduction
A top priority for all hospitals is patient safety, defined by the World Health Organization
(WHO) as an absence of preventable harm and the reduction of risk of unnecessary harm to a
patient throughout a hospitalization (WHO, 2020). A major component of patient safety
classified under this category is prevention of hospital-acquired pressure injuries (HAPIs), which
are considered “never-events” by the Joint Commission and align with the WHO as preventable
harm. Pressure injuries (PIs) are a National Database of Nursing Quality Indicator (NDNQI)
nursing-sensitive indicator (WHO, 2020). HAPIs can affect the overall hospital quality star
rating, which is an important measure of all hospitals open to the public. These star ratings can
either influence the reputation of the institution among the general population and the Magnet
status of an institution.
This quality improvement (QI) initiative addressed the high occurrence rate of HAPIs on
a particular unit in a hospital with Magnet status designation. The intent of this QI project was to
reduce HAPIs and improve patient outcomes through a technology-focused intervention.
Nursing-Sensitive Implications
HAPIs have been a nursing quality measure since the beginning of nursing, as evidenced
by Florence Nightingale’s text in Notes on Nursing published in 1859, “if he has a bedsore, it’s
generally not the fault of the disease, but of the nursing” (Nightingale, 1859). Since this time,
HAPIs have been a main focus of patient outcomes that can be directly related to nursing quality.
This is due to the fact that the majority of the preventative care for HAPIs is within the nursing
scope of practice. This includes topics such as having risk assessments documented, use of skin
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care products and the management of excessive moisture that can contribute to skin breakdown,
the mechanisms used to reposition and the frequency of the repositioning that occurs, and the
type of bed surface the patient is placed on all contribute to the development or prevention of
HAPIs (Lyder & Ayello, 2008). Due to these nursing responsibilities that play a large role in
HAPI prevalence, governing bodies of quality, such as NDNQI and The Magnet Program, use
occurrence rates of HAPIs to determine ratings and status of institutions, specifically related to
nursing.
The NDNQI is a national nursing quality measurement program that provides hospitals
with unit-level performance in comparison to state and national results (Agency for Healthcare
Research and Quality, 2014). Data is collected every three months on many different nursing
topics, such as falls, nosocomial infections, and pressure injuries, providing a clear
representation of nursing quality and the connectedness of nursing interventions with patient
outcomes. The results provide valuable evidence to support change, such as QI initiatives, as
well as provide data to accrediting organizations such as the Joint Commission and the Magnet
Recognition Program.
The Magnet Recognition Program, which includes the NDNQI measures, is awarded to
an organization that has an alignment of nursing leaders and nursing strategic goals to improve
the patient outcomes (American Nurses Credentialing Center, 2020). When an organization
becomes Magnet, nurses are empowered to reach their true potential, and the organization
demonstrates its ability to lead in healthcare change. Mayo Clinic Florida (MCF), an institution
that has committed to excellence, continues to maintain Magnet status as one of only 20 hospitals
within the state of Florida with this designation. Due to this commitment, innovation, evidenced-
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based research, and QI initiatives must be continually incorporated into practice to maintain
patient safety and top patient outcomes.
Financial Implications
In addition to quality organizations paying close attention, the Centers for Medicare and
Medicaid Services monitor pressure injuries as well (CMS, 2019). In 2008, CMS declared that
reimbursement would no longer be received for the care or treatment of pressure injuries that
develop throughout the hospitalization that are graded stage II or above (this excludes PIs present
on admission), in effect a reimbursement penalty for the organization. The CMS collects this
data from the NDNQI through quarterly pressure injury prevention surveys from hospitals across
the nation. This data then determines the unit-specific 50th percentile reimbursement benchmark
for pressure injuries.
This means if a unit is below the 50th percentile unit-specific national mean, there is no
reimbursement penalty incurred from CMS. The 50th percentile means for reimbursement in the
progressive care unit was 1.61% for the second quarter of 2019. This number was acquired from
quality data within the Mayo Clinic intranet derived from the NDNQI pressure injury prevention
survey data. The number of 1.61% sets the benchmark for CMS reimbursement at the institution,
which means a calculation of less than 1.61% pressure injuries that are a stage II or above within
the unit would meet this benchmark and not receive a financial penalty. Due to these existing
measures, not only are pressure injuries a very important quality indicator of nursing care, but
they can also become a source of financial burden for an organization.
Significance
The information above led to the development of this QI initiative to reduce the HAPI
occurrence rate on the progressive care unit (PCU) at Mayo Clinic in Jacksonville. In 2018, the
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PCU missed the 1.61% benchmark, which is the 50th percentile national mean average, with an
incidence rate of 8.33% of pressure injuries staged II or above. Again in 2019, the pressure
injury incidence rate was 3.85%, still above the NDNQI benchmark rate of 1.61%. The specific
number of PIs was 32 and 12 for the years 2018 and 2019, respectively. Currently, within the
first five months of 2020, there have been six total pressure injuries, trending toward missing the
1.61% benchmark rate again.
The PCU at Mayo Clinic has policies in place to prevent and reduce the occurrence of
HAPIs. These current practice policies include a full skin assessment on admission, or transfer
from another unit within the facility, with the nurse and the charge nurse. The use of the second
nurse during this assessment is to ensure that any wound or injury found on the patient is clearly
documented and relieves the unit of assuming responsibility for the injury. If the patient does
have a pressure injury on admission, the nurse is to inform the provider, place a wound/ostomy
care (WOC) consult, document the finding, and receive consent from the patient to photograph
the area. The WOC nurses will typically see the patient within 24 hours of admission and
provide recommendations, place nursing orders for wound care as needed, and order specialty
mattresses and other equipment as needed.
Secondly, current practice on the PCU requires an integumentary assessment using the
Braden Scale to be documented every shift or every 12 hours. This accounts for any changes in
the patient’s status that could affect the integumentary system. The Braden Scale has proven to
be a reliable tool to assess a patient’s risk for developing a pressure injury (Cox et al., 2018;
Hodl et al., 2019; Padula et al., 2018; Shieh et al., 2018; Yilmazer & Bulut, 2019). It addresses
six categories that the nurse must assess: sensory perception, moisture, activity, mobility,
nutrition, and friction/shear (see Appendix A). The scale gives results from six to 23, with those
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receiving lower numbers being more at risk for developing a PI. Currently, there is no further
action taken by the unit nurse if the result has decreased from the previous shift.
Lastly, it is standard practice on the unit to turn patients every two hours. There is no
formal responsibility between the nurse or patient care technician (PCT) regarding who initiates
this required task. Unfortunately, no data is available to demonstrate nurse or PCT compliance of
the scheduled two-hour turns on the unit. In general, evidence suggests around a 60%
compliance rate with patients being turned by every two by staff within hospitals across the
country (Pickham et al., 2016).
Due to the current policies and practices not proving to be effective at reducing the
incidence of HAPIs on the PCU as evidenced by missing the NDNQI unit-specific national
mean, the implementation of the FDA-cleared Leaf Patient Monitoring System was proposed
(Leaf Healthcare, 2020). This unique technology uses a sensor adhered directly to the patient to
monitor and document wirelessly, in real time, the patient’s position and movement, recognizing
both self-turns and staff-assisted turns. The device tracks the time spent in a specific position and
notifies staff via a central display when repositioning is necessary. The benefits of this
technology include increased prioritization of patient turning with a visual display indicating a
turn is needed, enhanced teamwork among staff without added communication effort, and real-
time documentation of patient positioning. The proposed QI project attempted to reduce the
trending NDNQI rates on the PCU while assisting nursing in adhering to the unit policy of the
every-two-hour turn protocol.
Purpose
As evidenced by the previous two years of data, current practice was not meeting the
benchmark set by CMS in the rate of HAPIs on the PCU. Due to the quality outcomes and
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financial implications associated with HAPIs, there was a need for improvement in the
prevention of HAPIs on the PCU at Mayo Clinic Jacksonville.
This QI initiative was based on the implementation of the Leaf Patient Monitoring
System to reduce the number of HAPIs on the PCU over the three-month implementation period.
The primary objective was proposed to be met by achieving a 70% reduction in HAPIs in
comparison to the six HAPIs that have already occurred in the first half of 2020. The secondary
objective that was measurable and assisted in meeting the primary objective was an improvement
in turning compliance. Baseline turning compliance rates for the PCU were not previously
tracked, however, literature suggests the average turning compliance rates among institutions
across the nation is around 60%, with even lower rates between 38 - 51% in ICUs (Pickham et
al., 2016). This secondary objective was proposed to be met by achieving an 85% turn
compliance rate, which is data that was directly collected from the Leaf technology.
Framework
Theoretical Framework
The QI framework that was used for the implementation of this initiative was a revised
version of the best practice framework (Nelson et al., 2010). The original framework was created
in 2007 to be a model for quality improvement, and targets four areas for success in quality
improvement: leadership; staff; performance and improvement; and information and information
technology. Within each domain are interventions to activate stakeholder participation in the
implementation of evidence-based practice. In 2014 this model was revised by a group of
physicians, nurses, and researchers from two different academic medical centers specializing in
pressure injury prevention to fit the needs of a pressure injury prevention QI initiative. The final
framework considered the four domains of the original framework and adapted the interventions
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to meet the requirements for a pressure injury improvement bundle. The basis of the original
framework is depicted in Appendix B, and the revised framework in Appendix C.
The interventions within each domain are directly parallel to the steps taken for the
implementation of the Leaf Patient Monitoring System. The QI interventions within the
leadership domain include prevention awareness, leadership initiatives, administration support,
and benchmarking. Mayo Clinic stakeholders and administration are aware of the past pressure
injury trends and supported the need for improvement within the PCU. This QI initiative itself
was a direct leadership initiative as the proposed project was fully supported by the unit nurse
manager, quality improvement nurse practitioner, and quality improvement nurse practitioner
within the ICU.
Within the staff domain of the framework, quality interventions implemented for success
included staff meetings, staff training, and prevention education. All three of these interventions
are addressed within dissemination of the QI project. In addition, performance measures are
included that will explain the “why” and the need for staff involvement of this intervention.
The performance and improvement domain includes the use of the Braden Scale as an
intervention, visual tools, and repositioning. These are all aspects included in the intervention.
The Braden Scale documentation by staff every 12 hours per Mayo policy was continued. The
visual tool intervention was incorporated through the Leaf Patient System Monitoring itself and
the central display showing the need for patients to be repositioned. This met the goal of the
framework to establish a formal regimen for patient repositioning.
Lastly, the information and information technology domains are evident within the
intervention through the Leaf Patient System Monitoring and its integration into the current
electronic health record (EHR) at Mayo Clinic. This proposed benefit of the technology would
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have allowed the suggested interventions of data tracking, automatic alarm, and EHR
implementation to be met. In addition, the proposed integration into the EHR would assist in
collecting data to assess the efficacy of the intervention.
Quality Improvement Model
The theoretical framework that was used in conjunction with the QI model was the
implementation method of Plan, Do, Study, Act. This is a tool that is used to organize and
evaluate a change. There are three keys to using this method correctly (Agency for Healthcare
Research and Quality, 2020). The first is evaluating a single step, which was the Leaf technology
for this QI. The next is doing it over a short duration of time, which was the three-month time
period for the QI. Lastly, using a small sample size, which was evident through the
implementation on one unit, the PCU, with hopes for expansion upon success on the QI.
Definition of Terms
Important phrases to understand within this proposed QI initiative are as follows:
1. Pressure injury: This is defined as damage to localized skin or underlying soft tissue that
typically presents over a bony prominence or from a medical device. There are four
stageable types of pressure injuries (1-4), unstageable pressure injuries, and deep tissue
injuries.
2. Hospital-acquired pressure injury or HAPI: This is a pressure injury, unstageable
pressure injury, or deep tissue injury that occurs while a patient is inpatient at a hospital.
3. Unstageable pressure injury: This is a pressure injury in which the base of the wound
cannot be visualized due to eschar or slough. Due to the unknown depth of the wound, it
cannot be categorized or staged.
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4. Deep tissue injury: This type of pressure injury presents as a purple or maroon
discoloration on intact skin or as a blood-filled blister (Cox et al., 2018).
5. Turn period: The Leaf Sensor will be programmed for a turn period of two hours. This
will allow the patient to stay in a single position for two hours and then will trigger the
alert by color on the display monitor to notify that a turn is needed within 15 minutes or
is due now. Once an adequate turn is performed, the technology will reset for another two
hour turn period.
6. Turn angle: This is defined as the rotation degree of the patient in the transverse plane in
relation to the patient’s vertical access (Schutt et al., 2017). The turn angle threshold for
this initiative is set at 20 degrees for all patients. This degree of turn must be met for the
sensor to accept the turn as sufficient and reset the turn period.
7. Decompression time: This is defined by a length of 15 minutes for this project. It means
that the next turn for the patient must give the previous pressure-loaded area on the body
at least 15 minutes before pressure being reapplied. The sensor will not reflect an
effective turn if pressure is reapplied to the same area, resulting in a continued red alert
on the central monitor.
8. Turning compliance: This is defined as a percentage of time that a patient was turned
within a 2-hour time frame. It is calculated by the time a patient was compliant of turning
within two hours divided by the total number of hours monitored. The turn compliance
percentage will be calculated by Leaf technology and provided in data report sheets.
Review of the Literature
A review of the literature was conducted and presented through a literature matrix
detailing the citation, purpose, design, sample, and results from the work (see Appendix D). The
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literature search was conducted through the databases ScienceDirect, Ovid Full-Text Nursing,
CINAHL, and Google Scholar. Keywords searched included pressure injury, prevention, patient
positioning, turning adherence, HAPIs, and Leaf Patient System Monitoring. Articles not
included were works that were completed outside the 5-year publication time frame, included
pediatric patients within the sample, did not discuss the interventions effect on HAPIs/PIs, or
were not published in English. Seventeen articles were selected for analysis to support the
proposed quality, 14 of which were within 5 years of publication. The three articles outside the
5-year publication period describe proper patient turning mechanics and its effect on pressure
injuries.
The main topics to be discussed for purposes of this QI project include literature
discussing different interventions that are common in practice to prevent pressure injuries, as
well as new approaches.
Risk Assessment
A consistent practice that emerged from the literature regarding the prevention of HAPIs
included a risk assessment performed upon admission and reassessed daily (Institute for
Healthcare Improvement, 2020). This practice is supported by governing groups such as the Joint
Commission, the National Quality Forum, and the Institute for Healthcare Improvement. Hodl et
al. (2019) conducted a cross-sectional prevalence study on 532 patients aged 65 years or older
that were at risk for HAPI development to determine if having a risk assessment completed
would lead to increased prevention interventions by nursing. They found that having a risk
assessment (a Braden Scale score in this study) documented is positively correlated with the
implementation of evidence-based interventions, such as the use of moisture/barrier creams for
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skin protection, malnutrition screenings, devices to promote pressure off-loading, and increased
mobilization and repositioning of the patient.
Another important pearl that arose from this study included nursing perceptions that
affect those who receive a risk assessment. The study found that the patients who did have
documented risk assessments were the older, more care-dependent patients within the study. In
contrast, they found that a younger, seemingly mobile patient that may appear to have little to no
risk of developing a pressure injury would be less likely have a pressure injury risk assessment
documented (Hodl et al., 2019). Based on their findings, the authors call for all patients,
regardless of perceived risk, to have a documented risk assessment, as this led to increased
compliance of prevention interventions on patients who otherwise may have been overlooked
(Hodl et al., 2019).
Another group reviewed the implications of a completed risk assessment (Braden Scale)
through a retrospective, descriptive study design (Cox et al., 2018). This study included 57
critically ill patients admitted to an intensive care unit for greater than 24 hours who acquired a
pressure injury during the admission. These patients all had Braden Scale score documented, but
still developed a pressure injury. This study’s findings suggest that a Braden Scale score is
necessary but fails to encompass all components that increase risk for development of the
injuries. Of note, the top two diagnoses out of the 57 patients that developed a pressure injury
were sepsis and respiratory failure, which are two statuses not addressed within the risk
assessment (Braden Scale) used in this study. Other factors such as prolonged intensive care unit
(ICU) admission, medical history including but not limited to diabetes, cardiovascular disease,
hypotension, and the need for mechanical ventilation may also be associated with increased risk
of HAPIs. Thus, critically ill patients who had a Braden Scale score documented and prevention
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strategies in place still developed a HAPI, suggesting that the condition of the patients left little
control over nursing quality to prevent the injury. While Cox et al. agreed that risk assessment
and aggressive prevention strategies in immobile, critically-ill patients is essential, the authors
postulated that some HAPIs were simply unavoidable.
Out of the 57 patients followed in the Cox et al. study, 40 patients, or 70%, developed a
deep tissue injury, (2018). While that study argued that some PIs are simply unavoidable, Li et
al. (2020) argued differently. Their systematic review and meta-analysis included 39 studies
published between 2008 and 2018 and included 2.5 million patients. This review stated that
superficial pressure injuries, stage I and II are the most common PIs to develop in hospitalized
patients, and are, in fact, preventable. The analysis completed by Li et al. emphasized the need
for continued attention to be given to HAPI prevention strategies as the global prevalence from
this extensive analysis proves that HAPIs continue to be a concern despite being unavoidable.
Turn Period
Another current practice discussed in the literature was the appropriate timing for the
patient turn period to give the highest chance of preventing a PI. The Prevention and Treatment
of Pressure Ulcers/Injuries: Clinic Practice Guideline developed by the European Pressure Ulcer
Advisory Panel, National Pressure Injury Advisory Panel, and Pan Pacific Pressure Injury
Alliance addresses the turn frequency within these guidelines (National Pressure Injury Advisory
Panel, 2019). Unfortunately, no exact period for repositioning has been connected with the
prevention of PIs. Instead, the guidelines suggest repositioning all patients with or at risk of a
HAPI on an individualized schedule. Also, it suggests that the risk assessment be done per the
acuity of the patient, with no specific frequency documented. The guidelines, however, did
analyze six level-one evidence studies within the repositioning section and concluded that
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different frequencies of repositioning (2, 3, or 4 hours) were at least somewhat effective at
preventing HAPIs. These guidelines were found to be true within the review of the literature
completed for this proposal (NPIAP, 2019).
Moore, Cowman, and Conroy conducted a multi-center, prospective, cluster-randomized
controlled trial in 2011 to assess the incidence of pressure injuries among older patients using
two different turn periods of 3-hour and 6-hour regimens. The study included two different
groups, the experimental group of 99 patients who were repositioned every 3 hours overnight,
and the control group of 114 patients who were repositioned every 6 hours (Moore et al., 2011).
The results concluded that three patients in the experimental group developed a HAPI compared
to 13 patients in the control group that developed a PI, which was statically significant (p =
0.035) in favor of the experimental group receiving the turn period of 3 hours (Moore et al.,
2011). This study did not address the acuity as the 2019 Clinical Practice Guidelines suggest.
However, it did find a favorable outcome with the experimental group.
Another study approached the turn frequency guidelines differently by using an
alternating approach and then analyzed its cost-effectiveness (Marsden et al., 2015). This study
was a systematic review of clinical data followed by an economic analysis using a cost-utility
model. The study evaluated 235 patients in a long-term nursing home over five weeks. The
sample was split into two groups, with one group receiving every four hours turns from semi-
fowlers to left or right lateral turns and the other group receiving four hours spent in semi-
fowlers followed by two hours in a left or right lateral turn. The results concluded that
intervention two, alternating between a four and two hour turn period, resulted in a reduction in
PIs when compared to the turn period of four-hour group. However, this intervention was not
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cost-effective. This study deemed that the number of prevented pressure injuries was small and
that the resource-intensive cost of this intervention was not cost-effective.
Multicomponent Interventions
Many studies within the literature review implemented a group of interventions to
prevent HAPIs. Shieh et al. (2018) performed a quality improvement project taking into account
risk assessment and other factors that can affect pressure injury development to implement a
multicomponent order set. The quality improvement project was implemented at two different
facilities between 2013 and 2016. The project intervention was a pink paper reminder system
that hung at the head of the bed for patients deemed at risk. The patients were deemed at risk in
one of two ways: a Braden score of less than or equal to 12, or a Braden score less than 18, plus
two of the following: older than 65 years of age, albumin level of less than or equal to 3.0 g/dL,
partially blanchable skin, irritant dermatitis, or the presence of a pressure injury. If the patient
qualified for the pink paper intervention, the nursing interventions included a sacral dressing,
heel protectors, a turn period of two hours, and a skin assessment every shift. The initiative
resulted in a 67% reduction in HAPIs when comparing data from 2009-2012 to 2013-2016. It
also showed a statistically significant reduction from 84 HAPIs over 101,600 patients days in
2013 to 32 HAPIs over 123,187 patient days in 2016. There are no data within the study to show
that one intervention was more effective than the other. However, it does follow many guidelines
discussed in the Clinical Practice Guidelines 2019. Another aspect to note within this study was
the intentional targeting of a smaller percentage of patients to qualify for the pink paper
intervention with the thought process that if all patients qualified, nursing would become
desensitized to the warning.
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A systematic review by Lin et al. (2019) revealed many more studies that chose to
implement a multicomponent pressure injury prevention package. A total of 21 peer-reviewed
papers (12 quality improvement projects and nine research papers) were included within the
review, with the number of prevention interventions between two and 11 (Lin et al., 2019). The
most common components implemented included clarification of staff roles, introducing new
roles, repositioning, staff and patient education, support surface use, pressure injury risk
assessment, skin assessment, nutrition needs assessment, documentation, multidisciplinary team
involvement, and mobilization. 12 of the 21 studied papers implemented a repositioning
intervention, 14 of the 21 implemented a risk assessment, and 16 of the 21 applied staff
education. The outcomes from all 21 studies were positive, but they did vary on the measurable
outcome. Five out of the nine research studies reported a significant reduction in pressure injury
prevalence, while the other four reported a favorable trending data toward reduction. Two
quality improvement papers reported savings of close to $1 million after the implementation of
the prevention strategies. Three studies reported increased compliance of prevention strategies.
Due to the positivity of outcomes that came from the studies, Lin concludes that implementation
of prevention programs for HAPIs are beneficial.
Another multicomponent intervention prevention strategy was analyzed through a quality
improvement project by Yilmazer and Bulut (2019). This initiative took place in an ICU to
determine the effectiveness of a pressure injury prevention algorithm on the prevention of
pressure injuries. The study included two sample groups, a pre-algorithm group (n = 80) and a
post-algorithm group (n = 74). The prevention algorithm was just that, an algorithm to guide the
care for prevention. If the skin was intact, daily skin assessment and daily Braden scale scoring
remained the standard of care. If the skin was not intact, with any type of inflammation, moisture
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or incontinence damaged skin, induration, or any skin loss, the nurse would continue on the
algorithm to determine if the injury was related to pressure, the stage of the injury, and the best
interventions to implement. The interventions at the end of the algorithm included the topics of
skincare, activity management, nutrition management, moisture/incontinence management, and
support surface management, with different interventions listed under each item. Of note, the
interventions included a turn period of two hours. The initiative revealed a statistically
significant positive outcome with a post-algorithm result of 9.21 PIs per 1,000 patient days in
comparison to the pre-algorithm prevalence of 46.10 pressure injuries per 1,000 patient days.
The study also evaluated staff feedback on the implementation of the algorithm and found that
73.3% of staff felt that the algorithm was sufficient, necessary, and useful for prioritizing
prevention measures throughout the shift.
Patient Monitoring Technology
In this section, nine works of literature will be discussed. The first four emphasize needs
in pressure injury prevention that the Leaf Patient Monitoring System can support directly. The
next four works include studies with the implementation of the technology. The final piece of
literature is an editorial that also addresses topics that can be related to success that can stem
from the technology implementation.
The first piece of literature to discuss here is a cost-utility analysis to compare the cost-
effectiveness of implementing pressure injury prevention-for-all patients versus ‘risk-stratified
prevention’ versus standard care (Padula et al., 2018). Risk-stratified prevention in this context
meant providing additional prevention interventions based on the Braden score of the patient.
Standard care was defined as intentional prevention of pressure injuries, but with no additional
interventions introduced. A Markov model was used to determine cost-effectiveness. It
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compared six different possibilities of prevention: prevention-for-all, with risk-stratified
prevention for patients that fell below a Braden score of 19, patients that fell below a Braden
score of 15, patients that fell below a Braden score of 13, patients that fell below a Braden score
of 10, and standard care. The results showed that prevention-for-all was most cost-effective
when compared with risk-stratified and standard care prevention.
Prevention-for-all produced higher quality-adjusted life years at a slightly higher cost, but
it yielded an incremental cost-effectiveness ratio of less than $100,000, meaning that the
difference was insignificant. The study explains that the prevention-for-all strategy was found
within this study for various reasons. The first being that a patient who could be identified as
low-risk has a reasonable chance of transitioning into a higher-risk category depending on any
status changes in the patient (Padula et al., 2018). Additionally, the thought of applying
prevention-for-all would cause this to become the new standard of care, thus decreasing costs
from this perspective. A limitation of the study is that there is no direct explanation of what
prevention-for-all is, but alludes to nursing hours spent for prevention, pressure-distributing
beds, and skincare or moisture management. Despite this limitation, it is reasonable to conclude
that the study suggests prevention-for-all provides better financial health to the institution as
opposed to risk-stratified prevention or standard care prevention.
The article discussed above ties directly into the next article. Saindon and Berlowitz
(2020) analyzed six articles published between 2018 and 2019 that brought forward important
“pearls” in terms of pressure injury prevention. In fact, the article by Padula et al. discussed
previously was one of these six. In addition to this article, one other article referenced pressure
injury prevention strategies are cost-effective for institutions. The article called for investment in
specialty mattresses, as this revealed a reduced incidence of PIs and had higher quality-adjusted
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life years (Nixon et al., 2006). Despite specialty mattresses not being the focus of this initiative,
it is apparent that investing in some sort of pressure injury prevention does bring about better
financial outcomes for institutions.
The next article is a descriptive, cross-sectional survey completed by healthcare workers
at institutions across Canada (LeBlanc et al., 2019). The purpose of the survey was to describe
HAPI prevention among different institutions, as well as identify opportunities for improvement.
The survey focused on the attitude of respondents toward PIs, the awareness of HAPI prevention
strategies, and practices implemented for prevention. The survey revealed that 85% of
respondents care for patients with pressure injuries, 90% confirmed awareness of prevention
devices, and 80% confirmed using these devices. The survey also revealed perceived pressure
injury prevention implementation barriers to include high nurse-to-patient ratios, resource
constraints, and less-than-optimal implementation of evidence-based practice. The conclusion
from this survey is the evidence of a disconnect between awareness of pressure injury prevalence
and strategical implementation to prevent pressure injuries.
An important aspect of pressure injury prevention is pressure itself. Peterson et al. (2010)
evaluated the effects of patient turning on skin-bed interface pressures through an observational
study using 15 adult employees at a university-affiliated hospital. The study was conducted using
sensor pressures from different positions of 15 adults who varied in age, weight, and body mass
index in a patient bed. Experienced intensive care unit nurses simulated patient turns on the
employees into the supine and lateral positions using pillow support, wedge support, and
different head-of-bed elevations. The results showed that raising the head of the bed to 30
degrees increased peak interface pressures with statistical significance. The study also revealed
that increased pressure developed when a wedge was used to reposition rather than a pillow.
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Another key point was an increase in pressure as weight and body mass index, but not height.
The overarching conclusion from this study was that despite the experience level of the staff
repositioning patients, there is not enough pressure off-loading to prevent skin breakdown and
pressure injuries. A limitation of this study is the date of publication a decade ago. However, the
information presented regarding skin-bed pressure would not be affected over time.
The next article is a randomized clinical trial that evaluates patient turning and the effect
on HAPIs in acutely-ill patients (Pickham et al., 2018). The trial has a sample of 1,312 patients
from two intensive care units assigned to either a control group or treatment group. The control
group of 653 patients received standard care practices that are in place within the unit. This is
explained within the study as pressure injury prevention “activities” but is not defined any
further. The treatment group of 659 patients received the implemented pressure injury prevention
intervention of turning every two hours with tissue decompression of 15 minutes. Both groups
were monitored with the application of a wearable patient sensor, a proprietary technology of
Leaf Healthcare. The primary outcomes of the study include the difference in compliance rates
of turning between the control and treatment group, as well as the prevention of pressure injuries
between the two groups. In total, there was 103,000 hours of monitoring data collected from the
wearable sensor between both groups. The intervention group showed statistically significantly
fewer HAPIs than the control group with 5 and 15 HAPIs occurring in each group respectively (p
= 0.031). In terms of the turning compliance, the treatment groups turning compliance was 67%
compared to the control group turning compliance of 54%. The conclusions based on this clinical
trial revealed that optimal turning and improved turning compliance time was effective in
reducing HAPIs.
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The next study examines the implementation of the patient monitoring device in a
nursing home setting and its effect on pressure injury prevention (Yap et al., 2019). The sample
included 44 residents that were monitored through the Leaf Sensor application for a range of two
to 21 days. The technology proved to significantly improve compliance with a turn period of two
hours for every patient (p = .0003). In addition, no new pressure injuries developed throughout
the study. The study also assessed staff perception of the technology using the Nursing Culture
Assessment Tool (NCAT). The results of the NCAT were not statistically significant, but they
did show improved teamwork and communication among staff with the implementation of the
technology.
The technology was successful in a long-term nursing facility and was also proven to be
successful on a medical unit in a community hospital (Schutt et al., 2017). This study again
evaluated the continual patient monitoring device (Leaf Sensor), but it used compliance with
patients turning every two hours as the measurable outcome. The sample included 138 patients
and a total of 7,854 hours of patient positioning data. The baseline data were derived from a
sample of 75 patients who had a sensor in place without a turning intervention. The post-
intervention sample of 63 patients also had the sensor in place and experienced staff-assisted
turns every two hours if the patient's self-turn was not a compliant turn, as evidenced by the
technology within the sensor. The study showed a baseline turn adherence of 64%, while the
post-intervention group showed a turn-adherence of 98%, which was statistically significant (p <
.001).
The final study examined was completed by Doucette et al. in and was found on the Leaf
Healthcare webpage. The purpose of this randomized controlled trial was to assess the use of
Leaf technology on turn adherence. Sixty-nine patients on a medical-surgical unit, which has a
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two hour turn period implemented on every patient as standard care, were monitored for 31 days
using the technology. The compliance of the turn period of two hours was calculated by the time
the patient was in accordance with the two-hour turn period divided by the total time the patient
was monitored. A total of 3,287 hours were monitored for all 69 patients. The average amount of
time monitored per patient was 47 hours. The study resulted in turn compliance of 88.5%.
The last piece of literature to be discussed in this review is an editorial written by Dr.
Joyce Black, who holds her Doctor of Philosophy in nursing and is also a certified wound care
nurse. Dr. Black discusses the 2014 International Clinical Practice Guidelines on pressure injury
prevention, as well as the clinical practice guidelines for prevention developed by the American
College of Physicians (ACP). Dr. Black pointed out that the 2014 International Clinical Practice
Guidelines contain only 77 statements with evidence-based literature as support, and the
remaining 498 statements are based on expert opinion (2015). Dr. Black then introduces the
guidelines written by the ACP, which are based on systematic reviews funded by The Agency for
Healthcare Research and Quality (2015) and contain only recommendations for the prevention of
pressure injuries based on supporting studies. She examined the differences between the two
sources to emphasize that there is a need for pressure injury prevention strategies founded in
literature and not just based on expert opinion due to the absence of valid evidence. She makes
two very valid points that are of value to this initiative. The first being that any type of pressure
injury risk assessment is of low sensitivity and specificity because the risk of the patient can
change within minutes based on the patient’s condition. This is a strong supporting statement for
the Leaf Patient Monitoring System as it is monitoring the patient continually, not for risk
assessment, but for ensuring that the patient is not put at a higher risk due to the patient’s
position (Black, 2015). Second, Dr. Black attributes the success of multicomponent prevention
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strategies to the engagement of leadership and administration, the involvement of direct care
providers, continuous education of staff, and sustained audits and feedback. The topics to which
she attributed success are all components that are proposed for implementation with the use of
Leaf technology.
Synthesis of Findings
The following is a summary of the findings from the review of the literature that was
applied in this QI project. The first suggestion was that risk assessments are necessary for all
patients (Hodl et al., 2019). Two other articles contained opposing views that risk assessment
does not assist in preventing unavoidable pressure injuries versus the conclusion that risk
assessment does help to prevent stage I and II pressure injuries (Cox et al., 2018; Li et al., 2020).
Taking into consideration the suggestions from this evidence, risk assessments using the Braden
Scale upon patient admission and every shift as the standard of care continued throughout the QI
as the literature shows evidence that they are effective in the prevention of pressure injuries.
Next, based on the literature reviewed for different turn frequencies, there was not a
specific turn period that had proven to be directly preventative of pressure injuries (Marsden et
al., 2015; Moore et al., 2011; Prevention and Treatment of Pressure Ulcers/Injuries: Clinic
Practice Guideline, 2019). Due to this, the implementation site standard care of every two hour
turns for patients, in addition to the turn period put in place in articles discussed above, 2 hours
remained the turn period for the QI (Doucette et al., 2014; Pickham et al., 2018; Schutt et al.,
2017; Yap et al.; Ly, 2019).
The next synthesized piece of evidence from the literature concludes that financial
investment into pressure injury prevention is cost-effective (Marsden et al., 2015; Padula et al.,
2018; Saindon & Berlowitz, 2020). Despite the evidence investing into various pressure injury
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prevention strategies, the overall theme among the literature is that pressure injury prevention is
cost-effective, therefore, supporting the investment into the Leaf Patient System Monitoring for
this quality initiative improvement.
Another piece of evidence founded in literature is that multicomponent pressure injury
prevention strategies are effective (Lin et al., 2019; Shieh et al., 2018; Yilmazer & Bulut, 2019).
While this quality initiative is not proposing to implement a multicomponent approach for
pressure injury prevention, the site of implementation does already use aspects of the
multicomponent approach as the standard of care, such as moisture/incontinence care, nutritional
management, and early mobilization. This piece of the literature, however, is an important aspect
to acknowledge for future prevention strategies.
Lastly, it was evident in the literature that the implementation of the Leaf Patient
Monitoring System is producing successful outcomes in terms of turn compliance and pressure
injury prevention (Doucette et al., 2014; Pickham et al., 2018; Schutt et al., 2017; Yap et al.,
2019). From these recent studies within the literature, this proposal is a promising testament to
stay on the cutting edge of research for the proposed implementation site and to improve patient
outcomes in terms of pressure injury prevention.
Project Description
The Leaf Patient Monitoring System was implemented on the progressive care unit
(PCU) at Mayo Clinic Jacksonville and analyzed over a three-month time period to assess the
technology’s effectiveness on reducing HAPIs.
Outcomes
The first proposed outcome was to reduce HAPIs by 70%. The comparison for meeting a
70% reduction is to the beginning of 2020 when the PCU already took responsibility of 6 HAPIs.
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In order to meet this outcome of the QI, the PCU must decrease by 70%, or by 4.2 HAPIs. This
comes out to being no more than 1.8 pressure injuries, which would round down to 1 pressure
injury throughout the three-month time period. The technology intended to assist in meeting this
goal through the color change alarm on the central monitor telling staff that the patient is due to
be turned, as well as through the technology taking into account turn angle allowing for tissue
reperfusion, which are both preventative measures for HAPIs.
The second proposed outcome was to improve the turn compliance on the PCU to 85%.
This meant that patients being monitored with the Leaf sensor would be repositioned every two
hours, a current unit policy, 85% of the time. This percentage result was calculated by the
technology using the number of hours monitored and the early, late, or on-time turning that took
place to provide an average of the turning compliance on the unit. This data was provided by the
technology company in daily, weekly, and monthly reports (see Appendix E). Prior to the QI,
there was no baseline data in which to compare the post-intervention turn compliance. However,
data suggests the average turn compliance across institutions in the nation is 38% - 66% (Leaf
Healthcare, 2017). Therefore, the second measurable outcome was to improve the turning
compliance to 85% on the PCU.
Intervention
The QI initiative was based on the implementation of the Leaf technology on the PCU.
The Plan, Do, Study, Act was the quality model that was followed for implementation.
Technology
The Leaf Patient Monitoring System is a proprietary medical software developed by Leaf
Healthcare to prevent hospital-acquired pressure injuries (Leaf Healthcare, 2020). It is composed
of a lightweight, wireless, wearable patient sensor and a central monitor that displays patients’
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positioning and movements (see Appendix F) through the use of secure antennas installed within
the unit that will directly communicate and document within the EHR used at Mayo Clinic. This
technology gave the PCU the opportunity to reduce the HAPI prevalence within the unit and
increase turning compliance. The central monitor display showed the room number, patient
initials, time until next turn, and current position (see Appendix G). The time until the next turn
is displayed using three colors: green, meaning the patient is in a good position; yellow,
indicating that repositioning is necessary within 15 minutes; and red, meaning that the patient is
overdue for repositioning. The Leaf Patient Monitoring System technology also takes into
account the turn angle to ensure that the turn is effective enough for pressure off-loading and
tissue reperfusion between turns.
Plan
The planning phase began in June for the quality initiative. The first step was reviewing
previous data of pressure injury prevalence on the PCU to prove a need for improvement.
Key Stakeholders
The next step was obtaining stakeholder commitment for implementation of the Leaf on
the PCU. This was done by crutching on the trial of the Leaf Patient Monitoring System that was
completed at MCF on both intensive care units in 2019 and has since been implemented as a unit
specific standard of care. Due to the success in the ICUs, the technology has been approved by
MCF and has gained administration, physician, and nurse-manager approval for implementation
on the PCU. Specifically, the clinical project manager for the ICU implementation is a Doctor of
Nursing Practice (DNP) specializing in quality at MCF. Another stakeholder that will be key to
QI project implementation is the nurse manager of the PCU who has also approved the project
implementation.
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The Leaf Patient Monitoring System has been thoroughly vetted and approved by the
administration for implementation within the PCU following the successful pilot in the ICU (see
Appendix H). The success of the ICU pilot, which demonstrated a reduction in HAPIs by 65%
and a projected financial savings profile of three million dollars a year based on the 2018 HAPIs
costs, are two of the influencing factors for expanding to the PCU.
Setting and Population
Due to the success of the trial in the ICUs at Mayo Clinic, the PCU, or step-down ICU,
was the logical next location for implementation. The PCU is a 27-bed unit composed of
critically ill patients. The census of the PCU is typically 24-26 patients a day with an average
length of stay of 5.4 days. The most common diagnoses on the unit include sepsis, congestive
heart failure exacerbation, chronic obstructive pulmonary disorder exacerbation, lung transplant,
and gastrointestinal bleeding. Many patients have impaired mobility due to illness or injury,
some requiring mechanical ventilation, or immobilization, rendering them unable to prevent a
potential pressure injury by turning independently. It was projected that 3-5 patients will be
monitored at any given time. Taking into account the average length of stay on the PCU, there
was projected to be about 15-30 patients a month that would be monitored on the sensor.
Application guidelines for use in the PCU were carried over from the ICU to ensure continuity
despite some interventions (such as vasopressors) not applicable to the PCU. The application
criteria pertinent to the PCU included: a pressure injury on admission, history of PI, a body mass
index of greater than 35 or less than 18, a Braden Scale score of less than 13, a stable spinal cord
injury, a rectal tube in place, moisture-associated skin damage, incontinence-associated
dermatitis, lower extremity flaccidity, and nursing judgement (see Appendix I). Patients who did
not qualify for the sensor included those with broken, irritated, or infected skin at or near the site
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of placement, a known allergy or sensitivity to medical-grade adhesives, a sternotomy incision
within the last seven days, and those who had an open chest wound. A quick reference guide or
“badge buddy” with the application criteria was given to each staff member to allow for easy
reference and evaluation of patients upon admission or transfer to the unit (see Appendix J).
Education
A large part of the planning phase included the education that was completed by the staff
on the PCU. This included nurses, PCTs, and health unit coordinators (HUCs). The first piece of
education was the eLearning provided by Leaf Healthcare. The vendor education session was
assigned to all staff within the MCF intranet. All staff was expected to complete this training
before the go-live date. The eLearning consisted of an 11 minute and 15 second training video
that demonstrated how to apply a Leaf sensor, register a patient, interpret the display, remove a
patient from the central display, and turn and reposition a patient effectively. The eLearning was
concluded by a 10-question multiple-choice exam that required an 80% pass rate for the
completion of the course. The data related to the completion of the education exam was not
recorded or of any use for the QI intiative, rather a step to prepare the staff for prior to
implementation.
The DNP student also worked with Leaf Healthcare staff to determine a schedule for
bedside in-service trainings the week prior to go-live. These trainings consisted of a 10-minute
in-service education led by the Leaf representatives for all nurses, patient care technicians, HUCs
on the use, application, and interpretation of the technology for efficient use. Staff was
responsible for attending the required education “drop-in” sessions without going above FTE.
The education sessions lasted only 10 minutes and was offered over 1 week, allowing staff to
attend during a scheduled shift and not go above the FTE. The completion of the in-service was
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ensured through a sign-in sheet. If a staff member was absent or unable to attend the session, the
DNP student gave an overview of the in-service to the specific staff member.
The HUCs also received an additional three-minute in-service regarding how to register
patients once a Leaf sensor is placed on the patient and the expected communication work flow.
The work flow was developed by the DNP student (see Appendix K). When the central display
indicates a patient is due for a turn in 15 minutes by turning yellow, the HUC was instructed to
send a text through the secure chat in Epic to the nurse and PCT. If the patient is not turned and
became overdue for a turn, indicated by turning red on the central display, the HUC was
instructed to call the nurse and PCT. If the patient was still not turned and was then 15 minutes
overdue, the HUC was instructed to call the TL to assist the nurse and PCT in getting the patient
turned. A copy of this workflow was laminated and located at the central monitor for easy access
by the HUC or any staff that looked at the monitor.
In addition to the floor staff being educated about the Leaf technology, the wound care
department was also involved. This department had already been educated on the Leaf
technology due to the implementation in the ICUs previously. The education needed for
implementation on the PCU included the communication workflow if a HAPI developed
throughout the study period. The protocol regarding a patient that is admitted with a pressure
injury or develops a HAPI during the hospitalization will still stay in place (consult to the WOC
team, notification to the provider, and consent to photograph the wound). If a HAPI did arise
during the QI period, the WOC nurse was to send an email communicating to the nurse manager,
which is current practice, and additionally include the DNP student about the presence of the
HAPI acquired during the hospitalization. The email communication did contain patient-
identifying information which is current practice and of use to the nurse manager, however, the
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DNP student did not keep track of any patient-identifying information. The DNP student only
used this communication to keep track of the HAPIs that occured throughout the intervention
time period.
Fiscal Consideration
The equipment needed for the implementation of the technology included the Leaf
Sensor, Leaf Antenna, and Leaf Dashboard. The Sensors had previously been invested in by
Mayo Clinic with an initial investment of 50 sensors for $200 each, which equated to about
$10,000 previously spent on sensors. The antennas, dashboard, and staff educational modules
were of no cost for implementation of the product. The installation of the technology was
completed within the scope of the information technology (IT) department, incurring no
additional costs on labor for the institution.
The educational module provided by Leaf included an 11-minute video with a post-test
that took staff a total of 20 minutes to complete. In addition to the eLearning, the bedside in-
service provided by the Leaf was completed in a 10-minute time period. These were both done
during a scheduled shift, however, for the effort expended by staff over the expected 30-minute
time period it took to complete both education requirements, it costed the institution around
$1,070. This calculation came from a half-hour of labor from 57 nurses averaging $30/hr, 24
PCTs averaging $15/hr, and 5 HUCs averaging $15/hr.
Confidentiality
There was no breach in the Health Insurance Portability and Accountability Act
throughout the entire process for the QI project as no patient identifying information was
recorded. All patients who qualify for sensor application were only tracked by the WOC nurse,
who reported on HAPIs as part of the current practice. If a HAPI did occur, the WOC nurse
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reported this to the nurse manager with details about the occurrence, which will now include
whether a Leaf sensor was in place or not. The DNP student also received this information,
however, the only data collected through the communication was that the HAPI occurred and
whether or not a Leaf sensor was in place. A running total of HAPIs was kept in a secure Excel
spreadsheet within the Mayo Clinic secure network during the QI (see Appendix L).
In addition, the data transmitted from the sensor to produce daily, weekly, and monthly
unit results contained no patient identifying information and was encrypted within the Mayo
Clinic secure network. The only data that was recorded from the report sheets produced by the
sensors for the QI initiative was the turning compliance percentages for the PCU during the
three-month time period. The compliance percentages were also recoded in an Excel spreadsheet
and kept within the Mayo Clinic secure network (see Appendix M).
Institutional Review Board Plan
The QI initiative met the criteria for facility IRB exemption due to less than minimal risk
with pressure injury prevention interventions. The Mayo Clinic IRB Wizard was used to prove
exemption (see Appendix N). The appropriate forms were completed for review at Jacksonville
University IRB as a quality improvement project. The QI was cleared by IRB on December 18,
2020 (see Appendix O).
Do
After the installation of technology, required eLearning, and bedside in-service education
was completed, the technology went live on the PCU. Staff used the Leaf workflow to guide
communication regarding the turning requirements, which was adhered to the central monitor for
easy access. Nurses that admitted or received a transfer patient that qualified for the application
of the sensor will receive a sensor from the team lead (TL). The TL is required to do a two-
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person skin check with the admitting nurse at time of arrival to the unit, therefore the TL was
responsible for bringing the Leaf sensor and encouraging its application if appropriate (see
Appendix I). The nurse then documented in the integumentary section on the report sheet that is
passed between nurses during shift change that the patient had the Leaf Sensor in place.
The DNP student initially received daily and weekly reports emailed from Leaf to ensure
the effective use of the technology by evaluating turn compliance time. Further intervention,
such as more education, was available if felt necessary by leadership or DNP student. The DNP
student also was available as a resource in person or by phone, in addition to the Leaf Healthcare
staff who was on-site during implementation the whole week of implementation, then weekly
after go-live.
Measures
During the three month implementation period, the DNP student was responsible for
keeping track of any HAPIs that developed to measure the first objective of a 70% reduction in
HAPIs. There were 6 HAPIs in the first five months of 2020, equaling 1.2 HAPIs a month. With
an average of 25 patients a day and an average length of stay of 5.4 days on the PCU, this
calculated to be about 140 patients per month. This made the incidence rate of HAPIs for the first
five months of 2020 equal 0.008. Once data is collected, the incident rate will be calculated by
using the average occurrence of HAPIs over the three-month time period divided by the total
number of patients monitored by the Leaf (see Appendix L). The goal will be met for this
objective if the calculated rate for the three-month time period is less than or equal to 0.0056, a
70% reduction in the incidence rate from the 0.008 rate calculated for the first five months of
2020. It will also be evaluated with a corresponding 95% confidence interval.
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The DNP student will also keep track of the monthly turning compliance percentage for
the unit resulting from the Leaf technology report sheets. This will be calculated using the
number of patients monitored on the Leaf per month (15-30 patients estimated) and the average
length of stay for each month. This will give the total number of patients days, then will be
multiplied by 12 turns (every 2 hours in a 24 hour day) to give the total number of turns that
should take place. The report sheet provided by Leaf will give a percentage for the turning
compliance which will then be used to calculate the actual turns that took place. The percentages
for the three months will be kept in an Excel spreadsheet to easily calculate the average of the
turning compliance over the three months to assess whether an 85% compliance rate was met or
not (see Appendix M).
Study
After the three-month evaluation period, the DNP student analyzed the data collected
throughout the intervention.
Evaluation Plan
The first outcome for the QI initiative is a 70% reduction in HAPIs on the PCU. In order
to meet this goal, the PCU must not be responsible for any more than one HAPI throughout the
three-month time period. This would be meeting the goal of a 70% reduction in HAPIs in
comparison to the six HAPIs that already occurred in the beginning of 2020. This achievement is
also in alignment with the NDNQI national mean and would incur no penalty on HAPI
reimbursement from CMS. This will be analyzed by addressing the Excel spreadsheet keeping
track of the running count of HAPIs throughout the three months (see Appendix L).
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Secondly, a turning compliance goal of 85% on the PCU is the next measurable outcome.
This will be evaluated using the average of the turning adherence percentages reported from the
statistics generated by Leaf. The data generated from the sensor will be reported to the DNP
student in a monthly report sheet (see Appendix E). The average of the three-month turning
compliance results will be calculated to determine whether an 85% turn compliance goal was
met or not (see Appendix M).
Act
Sustainability
The sustainability of this project will be evaluated once the three-month evaluation period
is complete. If the occurrence of pressure injuries are reduced and turning compliance is
improved, it will show that the Leaf Patient Monitoring System is effective. If this is the case, the
DNP student will present the data to the nurse manager of the PCU regarding the possibility of
continuing with the use of the technology. The DNP student will also make recommendations for
expansion to other units within the hospital. This will lead to further savings from HAPIs for
MCF and provide better outcomes for patients regarding preventable HAPIs. The DNP student
will also submit the final findings for publication and complete a DNP Final Defense
presentation.
Timeline
Below is an overview of the timeline for the QI initiative. It began in June 2020 and will
have a projected completion date of February 2021.
June 2020 – December 2020 (Preparation)
• Evaluate the need for improvement on PCU related to past pressure injury data
• Buy-in from stakeholders
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o Chief Nursing Officer
o Quality Nurse Practitioner
o PCU Nurse Manager
o WOC Team Lead
o Information Technology Manager
o Leaf Healthcare
• Complete proposal for implementation
o Review of Literature
o Project implementation plan
o Statistician consultation
o Create patient inclusion criteria
• Achieve IRB exemption from Jacksonville University and Mayo Clinic
• Technology installation by Leaf Healthcare
• Staff education
o Assigned e-learning course
o 10-minute in-service led by Leaf Healthcare staff
December 2020 – March 2021 (Implementation)
• Implementation of Leaf Patient Monitoring System on PCU
• Follow daily, weekly, and monthly reports generated from Sensor data
• Communication with WOC following HAPI data
• Intervene where needed for staff proficiency with the use of technology
March – April 2021 (Evaluation)
• Evaluate three-month data
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o Turn compliance
o Pressure injury prevalence
• Present findings to Jacksonville University DNP board
• Present the findings to Mayo Clinic (QI personnel, NM, and PCU staff)
• Submit findings for publication
• Upon results, determine dissemination onto other units within the hospital
Findings
The data collection included 24, 21, and 23 patients monitored respectively in the first,
second, and third set of four weeks throughout the three month time period. This equals a total of
68 patients monitored on the Leaf technology, within in the estimated number of 45 – 90 patients
included in the QI project. All patients included were admitted to the PCU at MCF, at least 18
years of age, and verbally agreed to allow staff to place the sensor on their chest for improved
turning compliance purposes based on the inclusion criteria and nursing judegement.
Objectives Met
The first objective proposed to be met with the QI was to reduce PIs by 70% which was
successful as evidenced through the incidence rate of 0 (see Appendix P). Throughout the three-
month data collection, there were zero documented pressure injuries related to turning on the
PCU. There were 7 pressure injuries that were responsibility of the PCU, hwoever, these
pressure injuries were due to medical devices, such as ace wraps on lower extremities and
respiratory equipment, that the Leaf technology was not meant to intervene with. An interesting
correlation found was that 6 of the 7 patients that developed medical-device related pressure
injuries had a Leaf sensor on throughout the hospitalization, but did not develop any HAPIs
related to turning.
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Objectives Not Met
The second objective proposed to be met throughout the implementation of this QI was
an overall turning compliance of 85%. This data was collected through daily reports generated
by the Leaf technology company and analyzed to produce an average over the three months. The
PCU had an average turning compliance of 76.67%, therefore not meeting the proposed outcome
(see Appendix Q).
Data Analysis
HAPI Data Analysis
The HAPI prevalence data was analyzed to evaluate if a 70% reduction in HAPIs
occurred or not. The objective was met if there is an incident rate less than or equal to 0.0056,
which comes from a 70% reduction of the 0.008 incidence rate calculated from the first five
months of 2020. Using the amount of patients monitored throughout the three-month data
collection time period, 68 patients with an average length of stay of 5.4 days totaled 367.2
patient days to evaluate, in comparison to the 675 patient days from the beginning of 2020 with 6
HAPIs. The 95% confidence interval for data pre-Leaf implementation based on a Poisson
distribution is (0.00326, 0.0193), or 3.26 – 19.3 events per 1000 patient days. The 95%
confidence interval for post-Leaf implementation based on a Poisson distribution is (0.0,
0.01004), or 0 to 10.0 events per 1000 patient days. Due to these intervals overlapping, there is
not a statistical difference at the 5% level of significance, however evidence does show a
difference (see Appendix R). In addition, the objective of a 70% reduction in HAPI occurences
was met with an incidence rate of 0.
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Turning Compliance Data Analysis
The turning compliance data was compiled from daily report sheets generated by the Leaf
technology company. Each daily turing compliance rate was kept track of in an Excel data spread
sheet by the DNP student. The monthly average and three-month averages were calculated using
simple arithmetic. The monthly compliances were 77.75%, 72.5%, and 79.75% resptively for the
first, second, and third four week sets during data collection. The overall average for the three-
month time period was 76.67% (see Appendix Q). Evaluating the data in quantiles shows that the
85% turn compliance goal was only met about 25% of the days during the data collection (see
Appendix S). Examining the data on a day-to-day basis shows the beginning and end with higher
daily turning compliances and the midle with lower compliance, in addition to two days of
outlying data (see Appendix T). The graphic examining the day-by-day data tells an interesting
story that the DNP student poses some explanation for in the next sections.
Facilitators and Positive Outcomes
The revised best practice framework that focused on pressure injury prevention was seen
greatly throughout the QI implementation period and assisted with the positive outcomes of the
QI greatly. Within the leadership and staff domains, many examples were seen throughout the
implementation period that respresented the ideas within these domains. Examples of staff
involvement that led to success started with the started with completion of the eLearning module
on the Leaf technology and attendance of the bedside in-service trainings, which both had 100%
completion rates on the PCU. The basic understanding of the technology and potential of
reducing PIs on the unit was greatly received by the staff. Secondly, a key facilitor of the QI was
the involvement of the nurse manager and team leaders on the unit, directly related to the
leadership domain of the framework used. This leadership group encouraged and educated the
REDUCING HAPIs
42
rest of the staff to initiate the Leaf sensor on appropriate patients, as well as troubleshoot when
necessary. Two examples of leadership involvement included adding the Braden Scores of the
patients on the unit to the team lead EMR view in order to facilitate the usage of the Leaf on
patients who had lower braden scores and increasing the number of pillows and wedges available
to staff at the beginning and throughout implementation to ensure the resources needed to
properly turn patients were available. These leadership examples are directly related to the
success of the initiative.
Another facilitator was the functionality that allowed staff to watch their patients on their
personal computer for the day, instead of having to walk to the central monitor displays at the
front and back of the unit. This allowed staff to constantly be aware of how much remaining time
was left until a patient needed to be turned. This successful aspect of the QI can be directly
accredited to the performance and improvement domain of the best practice framework that was
in use.
Some unintended positive outcomes throughout the QI time period was an overwhelming
sense of teamwork and communication. The HUCs were in constant communication with the
nurse and patient care tech regarding the patients that needed to be turned, as well as the nurse
and patient care technicians in communication amongst themselves. A major example of
teamwork was evident when a nurse or patient care tech would notice that a patient was due for a
turn and completed this task, not even being the primary caregivers for the patient. Both of these
improvements created a more positive work environement.
Barriers and Negative Outcomes
The most prevalent barrier throughout the QI project was user error when the patient
would either refuse a turn or when the patient was off the unit. A function on the central monitor
REDUCING HAPIs
43
display would allow the sensor to be paused, which would keep the overdue turn from affecting
the turing compliance, that was not well-understood by the HUC or staff and was rarely used
appropriately. The second barrier, which is greatly connected to the first, was when only one or
two patients were monitored at a time. This meant if that one or two patients was overdue for a
turn, either due to true lack of turning by staff, patient refusal, or patient being off the floor, the
turning compliance would plummet. This is the believed explanation for the outliers of 25%
turning compliance rates for two different days in the data analysis.
A second barrier was a lack of understanding of how to troubleshoot when a turn would
not register. Many times when the turns would not register as a turn it was due to the patient not
being turned far enough, and when the DNP student or team leader would assist the staff in
turning the patient, the turn was accounted for. This specific barrier did decrease toward the end
of three-month time period as staff learned the degree to turn a patient in order to achieve a full
turn.
Another barrier that was unexpected was the delay in communication between the Leaf
technology and the electronic medical record used at MCF. It was understood that the Leaf
technology would chart in the EMR when a patient was turned, however, this function was not
available at time of implementation or throughout data collectio on the unit. It is expected to be
interfaced with the EMR at some point this year. This was a frustrating factor as it could have
improved staff satisfaction and usage of the technology greatly. Unfortunately, this was the key
functionality of the technology that upheld the information and information technology domain
of the best practice framework that was not met.
Lastly, the DNP student believes the middle time period of data collection, which showed
less compliance than the beginning and end is due to the unavoidable effects of COVID-19.
REDUCING HAPIs
44
During this middle time period, PCU patients were displaced among different units as ICU
patients were moved into the PCU to accommodate the growing numbere of COVID-19 patients
within the facility. This led to a chaotic time in general for nursing and the focus on turing
compliance was decreased.
Adverse Events
Fortunately, there were no adverse patient outcomes reported throughout the
implementation, except complaints from patients that did not like to be turned every two hours.
One negative outcome that the DNP student had not predicted was staff members throwing away
sensors when unnecessary, such as when a patient went for MRI or simply because the sensor
became unattached. This decreased throughout the data collection time period as the DNP
educated staff on using a transparent dressing to replace the sensor instead of throwing it away
and using a new one. Lastly, an unintended negative outcome was the attitude toward the DNP
student from a few staff members for implementing the technology that focused on turning
patients every two hours, specifically at night. This was definitely not expected, but change,
especially in the work place, is very rarely well-accepted by all.
Recommendations
Due to the success of the reduction of PIs with this QI, it would be valuable to extend the
implementation of this technology to every unit within the hospital. The population at MCF
includes patients with many chronic medical conditions that are admitted to all units, therefore
providing an opportunity to improve turning compliance and ultimately reducing PI prevalence
throughout the entire hospital. Secondly, a recommendation for installing a central display in the
dialysis unit of the hospital would be beneficial. This would reduce the pause-time by at least 12
hours a week per patient, due to dialysis typically running for four hours, three days a week. This
REDUCING HAPIs
45
would not only improve the turning compliance, but continue to prevent chronically-ill patients
from developing a PI. Expanding the use of the Leaf technology throughout the entire facility
would further demonstrate that MCF is staying intune with the sophistication of technology in
healthcare and support the current Magnet status of the institution.
Another recommendation for the continued use of this technology throughout the hospital
would be to create a “super user” group of staff members who are well-edcuated on the
technology. The DNP student was the main and only resource for the technology, so whenever
the DNP student was working, trouble-shooting and assisting staff to better understand and use
the technology was very prevalent. However, the DNP was not there every day. Creating a
“super user” group would ensure that staff members have resources available in-person almost
every shift and would increase turning compliance and general understanding by staff.
Another recommendation that can be taken from this QI stems from the next step in the
DNP student’s career. As a future provider, the student has a deeper knowledge regarding the
detriment a PI can have on a patients health status, as well as overall quality of life. To focus on
prevention of HAPIs using the technology, the recommendation would be to include an order for
the application of the Leaf sensor be added to the admission orders on all patients. This order
would simply state to apply a Leaf sensor if the patient qualifies per the criteria or based on
nursing judegement. By making this a provider order, it would serve as a firm reminder to ensure
that staff thinks about using the Leaf on all patients necessary to further the benefit for patients
and the investement in the technology.
Discussion
The implementation of the Leaf Patient Monitoring System in the PCU at MCF
ultimately reduced the number of HAPIs for the 68 patients monitored over the three-month time
REDUCING HAPIs
46
period. This provides evidence that the reduction of HAPIs is indeed a nursing-sensivity quality
measure, as Florence Nightingale brilliantly declared long ago. In addition to the HAPI reduction
being a reflection of the nursing quality at MCF, it also assists in reducing the financial stress
that HAPIs can place on an institution. MCF has improved the quality of care the patients
receive, decreased the chance of reimbursement penalties by CMS, and decreased the out-of-
pocket expenses that come with HAPIs with the use of this technology. The expansion of use of
the Leaf technology would benefit the future patient population, the facility as a whole, and
reflect the leadership of the institution in healthcare innovation.
REDUCING HAPIs
47
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Appendix A
Braden Scale
REDUCING HAPIs
53
Appendix B
Best Practice Framework
REDUCING HAPIs
54
Appendix C
Best-practice framework of quality improvement interventions for pressure ulcer prevention in
hospitals
Running head: REDUCING HAPIs 55
Appendix D
Review of Literature
Year Author, Title, Journal Purpose Design Pearls
2015 Black, J., (2015). Pressure
ulcer prevention and
management: a dire need for
good science. Annals of
Internal Medicine.
https://doi.org/10.7326/M15-
0190
Discuss current PI practice
from 2014 International
Clinical Practice Guidelines
and American College of
Physicians
• The 2014
international clinical
practice guideline on
pressure ulcer
prevention and
treatment includes
only 77 statements
with evidence to
support them,
whereas the
remaining 498
statements are based
on expert opinion
Editorial • ACP provides guidelines on systematic reviews
funded by AHRQ.
• the low sensitivity and specificity of pressure
ulcer risk assessment are expected because risk
can change within minutes. These varying risks
are not captured unless the risk assessment tool
is completed contemporaneously with changes in
patient condition.
• The success of multicomponent interventions in
reducing pressure ulcer incidence is believed to
be attributable to their engagement of leadership
and administration, involvement of direct care
providers, continuous education of staff, and
sustained audits and feedback
REDUCING HAPIs
56
Year Author, Title, Journal Purpose Design Sample Result
2018 Cox, J., Roche, S., &
Murphy, V. (2018).
Pressure injury risk factors
in critical care patients: a
descriptive analysis.
Advances in Skin & Wound
Care, 31(7), 328-334.
To describe the
risk factors
associated with
PI development
in a sample of
medical-surgical
intensive care
unit patients and
determine
whether these
risk factors were
congruent with
the risk factors
proposed in the
work of the
National
Pressure Ulcer
Advisory Panel
on unavoidable
PIs
Retrospective,
descriptive design
• 57 critically ill patients
admitted to the
medical-surgical
intensive care unit for
more than 24 hours and
who acquired a PI
during their admission
• immobility (n = 57
[100%]), septic shock
(n = 31 [54%]),
vasopressor use (n = 37
[65%]), head-of-bed
elevation greater than
30- (n = 53 [93%]),
sedation (n = 50
[87.7%]), and
mechanical ventilation
for more than 72 hours
(n = 46 [81%]).
• Top two diagnoses
were sepsis and
respiratory failure
Use of Braden scale for PI risk
assessment is current use, but does
not account for many other risk
factors of this population
(advanced age, prolonged ICU
admission, medical history [DM,
CV disease, hypotension],
mechanical ventilation,
vasopressor agents, decreased
mobility/activity.
While the implementation of ag-
gressive prevention strategies is
essential to reducing PI prev-
alence, it is also important to
recognize that certain clinical
conditions may result in exposure
to risk factors that go be- yond the
scope of prevention
REDUCING HAPIs
57
Year Author, Title, Journal Purpose Design Sample Result
2014
Doucette, M., Adams, S.,
Cosdon, K., & Payne, K.,
(2014). “Drive to zero”:
using wearbale technology
for pressure ulcer
prevention on a medical-
surgical unit.
To assess use of
new technology
to identify turn
adherence
Pragmatic, multi‐center, open label,
prospective,
cluster‐randomized
controlled trial
• Sixty-nine patients with
mean Braden score of
19.4 (min 13, max 23)
were monitored over 31
days. A total of 3287
hours of monitoring
data was collected.
Average monitoring
time per patient was 47
hours
• The average compliance to the
two-hour turn protocol was
88.5% (min 82%, max 99%).
There were a total of 292 turn
alerts. Twelve patients (17%)
never had a turn alert, ten of
whom had Braden scores above
18.
REDUCING HAPIs
58
Year Author, Title, Journal Purpose Design Sample Result
2019 Hodl, M., Eglseer, D., &
Lohrmann, C. (2019).
Does conducting a risk
assessment facilitate better
care for patients at risk of
pressure injuries?.
Advances in Skin & Wound
Care, 32, 365-369.
To evaluate if
the use of a
pressure injury
(PI) risk
assessment is
associated with
the more
frequent use of
international
evidence-based
guideline
interventions in
patients at risk
of PI.
Multicenter cross-
sectional
prevalence study
• 532 patients 65 years at
risk of PI or older in
Austrian hospitals
Conducting and documenting a
risk assessment led to more
recommended interventions being
performed
These findings show that
conducting and documenting a risk
assessment were positively
correlated with the more frequent
use of internationally
recommended PI prevention
measures, such as the provision of
moisture/barrier cream, use of
mobilization specific for PI,
malnutrition screening, and
floating heels/ heel suspension
devices
These findings are in line with
international guidelines, which
highly recommend that a risk
assessment be conducted within 8
hours of admission for all patients.
REDUCING HAPIs
59
Year Author, Title, Journal Purpose Design Sample Result
2019 LeBlanc, K., Woo, K.,
Bassett, K., & Botros, M.,
(2019). Professionals’
knowledge, attitudes, and
practices related to
pressure injuries in
Canada. Advances in Skin
& Wound Care, 32(5),
228-233.
To describe the
pattern of PI
prevention and
identify national
priorities and
opportunities to
address PIs.
Descriptive, cross-
sectional, online
survey
590 surveys were
completed
• Eighty-five percent of respondents
confirmed that PIs occur in their
work environments. Most of the
respondents (91%) confirmed that
they were part of a team that treats
PIs. Of the 590 participants, 90%
confirmed that they are aware of PI
prevention devices and technologies.
Between 80% and 90% attest to
using offloading devices including
prophylactic dressings to prevent
PIs, but only 20% instituted
measures to address moisture-
associated skin damage.
• It is evident that, although the
majority of respondents were aware
of PIs and related treatment
protocols, barriers still exist that
impede optimized care and
treatment.
• There are three main barriers to
effective and optimized PI care:
organizational, provider, and patient
barriers.
• PI treatment barriers include high
nurse-to-patient ratios, resource
constraints, and insufficient
integration of best practices into
organizational structures and
processes.
• Evidence-informed strategies to
promote skin health and reduce the
incidence of skin breakdown are
integral to safeguard patient safety,
quality of care, and judicious use of
healthcare resources.
REDUCING HAPIs
60
Year Author, Title, Journal Purpose Design Sample Result
2020 Li, Z., Lin, F., Thalib, L.,
& Chaboyer, W. (2020).
Global prevalence and
incidence of pressure
injuries in hospitalized
adult patients: a systematic
review and meta-analysis. International Journal of Nursing Studies, 105.
To
systematically
quantify the
prevalence and
incidence of
pressure injuries
and the hospital-
acquired
pressure injuries
rate in
hospitalized
adult patients
Systematic review
and meta-analysis
• Studies with
observational, cross-
sectional or
longitudinal designs,
reporting pressure
injury among
hospitalized adults
(≥16 years) and
published in English
• 42 were included in
the systematic review
and 39 of them were
eligible for meta-
analysis, with a total
sample of 2,579,049
patients
• Medline, PubMed,
Embase, Cochrane
Library, CINAHL and
ProQuest databases
from January 2008 to
December 2018
• study suggested that the burden
of pressure injuries remains
substantial with over one in ten
adult patients admitted to
hospitals affected
• Superficial pressure injuries,
such as Stage I and II, are most
common stages and are
preventable. Thus, healthcare
providers need to take ac- tions
in preventing superficial stages
from occurring or worsening
• highlight healthcare institutions’
focus on pressure injuries
globally and supports the need
to dedicate resources to
prevention and treatment on
pressure injuries
• The burden of pressure injury
was identified to be substantial
with the overall prevalence of
12.8% in hospitalized adult
patients
REDUCING HAPIs
61
Year Author, Title, Journal Purpose Design Sample Result
2019
Lin, F., Wu, Z., Song, B., Coyer,
F., & Chaboyer, W. (2019). The
effectiveness of multicomponent
pressure injury prevention
programs in adult intensive care
patients: a systematic review.
International Journal of Nursing
Studies, 102, 1-14.
https://doi.org/10.1016/j.ijnurstu.
2019.103483
Evaluate the
effectiveness of
pressure injury
prevention
programs in re-
ducing pressure
injury
prevalence and
incidence in
the adult
intensive care
population
Systematic
Review
Twenty-one peer
reviewed papers
Common components of
the programs included:
clarification of staff
roles, introducing new
roles, repositioning, staff
and patient education,
support surfaces use,
pressure injury risk
assessment, skin
assessment, nutrition
needs assessment,
documentation,
multidisciplinary team
involvement, and
mobilization.
• Five of the eight research
studies and one of the
quality improvement
projects reported
significant decrease in
pressure injury
prevalence, and/or
increase in compliance to
pressure in- jury
prevention protocols and
strategies.
REDUCING HAPIs
62
Year Author, Title, Journal Purpose Design Sample Result
2015 Marsden, G., Jones, K.,
Neilson, J., Avital, L.,
Collier, M., & Stansby, G.
(2015). A cost-
effectiveness analysis of
two different repositioning
strategies for the
prevention of pressure
ulcers. Journal of
Advanced Nursing.
To assess the
cost effectiveness
of two
repositioning
strategies and
inform the 2014
National Institute
for Health and
Care Excellence
clinical guideline
recommendations
on pressure ulcer
prevention.
Economic analysis
took the form of a
cost-utility model
Systematic review
of clinical data
235 patients evaluated over
5 weeks from nursing
home
Intervention 1: 4 hours in a
semi-Fowler 30° position
and 4 hours in a lateral
position 30°. The semi-
Fowler position consisted
of a 30° elevation of the
head end and the foot end
of the bed. In a lateral
position, the position, the
patient was rotated 30°,
with their back supported
with an ordinary pillow.
Intervention 2:
Repositioning was the
same as above but with 4
hours spent in the semi-
Fowler 30° position
alternating with 2 hours in
a lateral 30° position.
Patients in both groups
were lying on a visco-
elastic foam overlay
mattress
• We do not know that
intervention 1 is a cost-
effective strategy compared
with all other possible
repositioning strategies, only
that intervention 2 is not cost
effective compared with
intervention 1.
• Alternating was not cost-
effective
REDUCING HAPIs
63
Year Author, Title, Journal Purpose Design Sample Result
2011
Moore, Z., Cowman, S., &
Conroy, R.M., (2011). A
randomized controlled
clinical trial of
repositioning, using the 30
degree tilt, for the
prevention of pressure
ulcers. Journal of Clinical
Nursing, 20, 2633-2644.
Doi: 10.1111/j.1365-
2702.2011.03736.x
To compare the
incidence of
pressure ulcers
among older
persons nursed
using two
different
repositioning
regimens
Pragmatic, multi‐center, open label,
prospective,
cluster‐randomized
controlled trial
• The experimental group
(n = 99) were
repositioned three
hourly at night, using
the 30° tilt; the control
group (n = 114)
received routine
prevention (six-hourly
repositioning, using 90°
lateral rotation)
• Three patients (3%) in the
experimental group and 13
patients (11%) in the control
group developed a pressure
ulcer
• Repositioning older persons at
risk of pressure ulcers every
three hours at night, using the
30° tilt, reduces the incidence of
pressure ulcers compared with
usual care
REDUCING HAPIs
64
Year Author, Title, Journal Purpose Design Sample Result
2018
Padula, W.V., Pronovost,
P.J., Makic, M.B.F., Wald,
H.L., Moran, D., Mishra,
M.K., & Meltzer, D.O., (-
2018). Value of hospital
resoures for effective
pressure injury prevention:
a cost-effectiveness
analysis. BMJ of Quality
and Safety, 28, 132-141.
doi:10.1136/bmjqs-2017-
007505
Analyze the
cost-utility of
performing
repeated risk-
assessment for
pressure-injury
prevention in all
patients or high-
risk groups.
Cost-utility
analysis using
Markov modelling
from US societal
and healthcare
sector perspectives
within a 1-year
time horizon
• three different
pressure-injury
prevention strategies
• (a) prevention
guidelines applied to
all patients daily (ie,
‘prevention-for-all
patients’)
• (b) providing ‘risk-
stratified prevention’
only to patients below
certain categorical
Braden score
thresholds (eg,
minimal-risk,
moderate-risk, high-
risk);
• (c) standard care for all
patients in which
compliance is variable
as noted previously by
Padula and colleagues
• Analysis using EHR data maintains
that pressure-injury prevention for
all inpatients is cost- effective
• Prevention-for-all would be a cost-
effective strategy for most Western
societies since prevention-for-all
was the most costly but also the
most effective strategy.
• Additionally, it may also be true
that by applying the same care
process to all patients, the process
becomes standardized, done more
efficiently and easier to monitor
and assure improved process
reliability.
• Therefore, it makes sense for
health systems to invest in quality-
improvement infrastructure
• Targeting prevention guidelines to
patients with Braden scores of less
than 15, 13, or 10 were all found to
be domi- nant when compared with
standard care. This means that it
both saved money and yielded
higher quality-adjusted life-years
(QALYs).
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65
Year Author, Title, Journal Purpose Design Sample Result
2010 Peterson, M.J., Schwab,
W., Oostrom, J.H.,
Gravenstein, N., & Caruso,
L.J., (2010). Effects of
turning on skin-bed
interface pressures in
healthy adults. Journal of
Advanced Nursing, 66(7),
1566-1564. doi: 10.1111/
j.1365-2648.2010.05292.x
To study of the
effects of lateral
turning on skin-
bed interface
pressures in the
sacral,
trochanteric and
buttock regions,
and its effec-
tiveness in
unloading at-risk
tissue
Descriptive,
observational
study
• 15 healthy adults
(employees) from
a university-
affiliated hospital
• Interface pressure
profiles were
obtained in the
supine position,
followed by
lateral turning
with pillow or
wedge support
and subsequent
head-of-bed
elevation to 30°.
• Standard turning by experienced
intensive care unit nurses does not
reliably unload all areas of high
skin-bed interface pressures. These
areas remain at risk for skin
breakdown, and help to explain why
pressure ulcers occur despite the
implementation of standard
preventive measures
• Raising the head-of-bed to 30° in the
lateral position statistically sig-
nificantly increased peak interface
pressures and total area ‡32 mmHg.
Comparing areas ‡32 mmHg from
all positions, 93% of participants
had skin areas with interface
pressures ‡32 mmHg throughout all
positions (60 ± 54 cm2), termed
‘triple jeopardy areas’ meaning
supine, left-turned, right-turned. The
triple jeopardy area increased
statistically significantly with
wedges as compared to pillows
• At-risk areas were statistically larger
with wedges than with pillows at the
lateral left and elevated left positions
• No trend emerged upon analyzing
peak interface pressures as height,
weight or BMI increased. However,
for at-risk areas, an increasing trend
began to emerge as weight and BMI
increased, but not height
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66
Year Author, Title, Journal Purpose Design Sample Result
2018
Pickham, D., Berte, N.,
Pihulic, M., Valdez, A.,
Mayer, B., & Desai, M.,
(2018). Effect of a wearable
patient sensor on care delivery
for preventing pressure injuies
in acutely ill adults: A
pragmatic randomized clinical
trial. International Journal of
Nursing Studies, 80, 12-19.
doi:
10.1016/j.ijnurstu.2017.12.012
To evaluate
whether optimal
patient turning,
defined as
regular turn- ing
every 2 h with
at least 15 min
of tissue
decompression,
reduces HAPUs
in acutely ill
patients.
Randomized
clinical trial • 1312 total patients;
653 in control group
receiving standard
practices; 659
receiving optimal
turning practices.
• All subjects will
receive a wearable
patient sensor
• Optimal pressure ulcer
prevention is defined
as regular turning
every 2 h with at least
15 min of tissue
decompression
• 103,000 h of monitoring data.
• Treatment group with 5
HAPIs, control group with 15
HAPIs
• Turning compliance of 67% in
treatment group vs 54% in
control group
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67
Year Author, Title, Journal Purpose Design Sample Result
2020 Saindon, K. & Berlowitz,
D.R. (2020). Update on
pressure injuries: a review
of literature. Advances in
skin and wound care, 33,
403-409. doi:
10.1097/01.ASW.
0000668552.48758.1c
To provide
information
about the latest
evidence-based
practice related
to pressure
injuries
Literature Review 6 articles published in 2018
and 2019 that represent
importance of PI
prevention
• Pressure injury prevention is
cost-effective
• Nixon et al. discusses specialty
mattresses as cost-effective
strategies to prevent PIs
• References the Padula et al.
article and cost-effectiveness
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Year Author, Title, Journal Purpose Design Sample Result
2017
Schutt, S.C., Tarver, C., &
Pezzani, M., (2017). Pilot
study: Assessing the effect
of continual position
monitoring technology on
compliance with patient
turning protocols. Nurse
Open, 5(1), 21-28.
The study aim
was to evaluate
if continual
patient position
monitoring,
taking into
account self-
turns and
clinician-
assisted turns,
would increase
the percentage
of time a
patient’s
position
changed at least
every 2 hr
Inpatient, non-
randomized, pre-
/postintervention
study
• Data collected May
2013–February 2014
on a 39-bed medical
unit in a community
hospital
• 138 patients across
both phases were
included in the
analysis, representing
7,854 hr of position
data.
• The baseline phase
sample (N = 75)
consisted of a different
set of patients than did
the postintervention
phase sample (N = 63).
T test results revealed lower
baseline phase turn adherence of
39%–89% (average 64%)
compared with post-intervention
phase turn adherence of 86%–
100% (Mean 98%). The
improvement in turn protocol
adherence was statistically
significant (p < .001).
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Year Author, Title, Journal Purpose Design Sample Result
2018 Shieh, D., Berringer, C.M.,
Pantoja, R., Resureccion,
J., Rainbolt, J.M., Hokoko,
A. (2018). Dramatic
reduction in hospital-
acquired pressure injuries
using a pink paper
reminder system. Advances
in Skin & Wound Care,
31(3), 118-122.
To reduce the
number of
hospital-acquired
pressure injuries
(HAPIs) by
flagging
extremely high-
risk patients with
a pink paper
reminder system
and
implementing a
pressure injury
prevention order
set.
Quality
improvement
project
All adult patients admitted
to two different hospitals
over nearly 4 years meeting
one of two criteria:
1. A Braden score of
12 or less.
2. A Braden score
less than 18 and
any 2 of the
following: age 65
years or older,
albumin level less
than or equal to 3.0
g/dL, a preexisting
pressure injury,
and skin at risk
(Table 1). Skin at
risk was defined as
any of the
following:
moisture
dermatitis, irritant
dermatitis,
blanching skin,
skin tears, and
traumatic wounds.
• 67% reduction in quarterly
HAPI rate from a mean of 1.2
HAPIs per 1000 patient-days
(measured during the first
quarter of 2009 to the fourth
quarter of 2012) to 0.4 HAPIs
per 1000 patient-days (measured
during the first quarter of 2013
through the fourth quarter of
2016).
• In 2009, there were 138 HAPIs
over 96,429 patient-days. In
2013, the year the pink paper
program was initiated, there
were 84 HAPIs over 101,600
patient-days. In 2016, the total
number of HAPIs was 32 cases
over 123,187 patient-days.
• This system was designed to
target 10% to 15% of the
hospital population. Using only
Braden scores less than 17
would encompass a much larger
percentage of the hospital
population. It is hypothesized
that this quality im- provement
project would not have been as
successful if a ma- jority of the
hospital patients were flagged as
high risk because the nursing
staff would most likely have
become desensitized to the
warning system.
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70
Year Author, Title, Journal Purpose Design Sample Result
2019 Yap, T.L., Kennerly, S.M.,
& Ly. K., 2019. Pressure
injury prevention:
outcomes and challenges to
use of resident monitoring
technology in a nursing
home. Journal of Wound,
Ostomy, and Continence
Nursing, 46(3), 207-213.
To examine the
usability, user
perceptions, and
nursing
occupational
subculture
associated with
introduction
of a patient
monitoring
system to
facilitate
nursing staff
implementation
of standard care
for pressure
ulcer/injury
prevention in
the nursing
home setting.
• Forty-four residents
were monitored for 2 to
21 days
•
• System use significantly (P =
.0003) improved compliance
with every 2-hour repositioning
standards.
• Prior to the study, the 3-month
facility-acquired PrI prevalence
rate was 7.3% (national average:
7.4%)
• Mean repositioning compliance
during the intervention period
was significantly higher than the
baseline period (t= 4.42, P=
.0003), with significant
improvements on the 3 pm to 11
pm (P=.02) and 11 pm to 7 am
shifts (P < .0001). No new PIs
developed during the baseline or
intervention periods.
• The overall NCAT (nursing
culture assessment tool for use
in LTAC) scores, although not
statistically signi - cantly di
erent before and after
implementation, suggested the
potential of PM system for
improving teamwork and com-
munication.
REDUCING HAPIs
71
Year Author, Title, Journal Purpose Design Sample Result
2019 Yilmazer, T. & Bulut, H.
(2019). Evaluating the
effects of a pressure injury
prevention algorithm.
Advances in Skin & Wound
Care, 32(6), 278-284.
To evaluate the
effect of a
pressure injury
prevention
algorithm on
pressure injury
prevention.
Quality
improvement
All patients older than 18
years (prealgorithm, n =
80; postalgorithm, n = 74)
Interventions included skin
care, nutrition
management,
moisture/incontinence
management, support
surface management, and
activity management
Activity management
included: q2 turns, 30
degree turn angle, no
rotation to area of redness,
do not place on medical
device, do not place in
semi-seated position, and
support extremities
• The pressure injury incidence
was 46.10 per 1,000 patient-
days in the prealgorithm
period and 9.21 per 1,000
patient-days in the
postalgorithm period. The
decline was statistically
significant (z = 9.590, P G
.001).
Running head: REDUCING HAPIs 72
Appendix E
Leaf Healthcare Reports
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Appendix F
Leaf Patient Monitoring Sensor
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Appendix G
Leaf Central Monitor Display
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Appendix H
Approval for Leaf expansion to PCU
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Appendix I
PCU Sensor Application Criteria
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Appendix J
Application criteria “badge buddy”
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Appendix K
Communication Work Flow
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Appendix L
HAPI data collection Excel spreadsheet
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Appendix M
Turning compliance data collection Excel spreadsheet
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Appendix N
Mayo IRB exemption letter
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Appendix O
JU IRB submission approval
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Appendix P
HAPI Data
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Appendix Q
Turning Compliance Data
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Appendix R
HAPI Poisson Distribution
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Appendix S
Turning Compliance Quantile Data
100.0% maximum 95
99.5% 95
97.5% 93.875
90.0% 88
75.0% quartile 85.75
50.0% median 77.5
25.0% quartile 69
10.0% 64
2.5% 46.875
0.5% 44
0.0% minimum 44
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Appendix T
Turning Compliance Day-by-Day Data
